Predictive models of sarcopenia based on inflammation and pyroptosis-related genes.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39777262", "kind": "science-record", "revision": 3, "content_hash": "sha256:7fba338c475b585667e6c3377ae304287750a1ccf9d6391c57684fa82133c0c4", "created_at": "2026-11-01T20:30:06Z", "updated_at": "2026-11-01T22:13:30Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Predictive models of sarcopenia based on inflammation and pyroptosis-related genes.", "doi": "10.3389/fgene.2024.1491577", "pmid": "39777262", "authors": ["Xiaoqing Li", "Cheng Wu", "Xiang Lu", "Li Wang"], "journal": "Frontiers in genetics", "year": 2024, "abstract": "Background: Sarcopenia is a prevalent condition associated with aging. Inflammation and pyroptosis significantly contribute to sarcopenia.\nMethods: Two sarcopenia-related datasets (GSE111016 and GSE167186) were obtained from the Gene Expression Omnibus (GEO), followed by batch effect removal post-merger. The \"limma\" R package was utilized to identify differentially expressed genes (DEGs). Subsequently, LASSO analysis was conducted on inflammation and pyroptosis-related genes (IPRGs), resulting in the identification of six hub IPRGs. A novel skeletal muscle aging model was developed and validated using an independent dataset. Additionally, Gene Ontology (GO) enrichment analysis was performed on DEGs, along with Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and gene set enrichment analysis (GSEA). ssGSEA was employed to assess differences in immune cell proportions between healthy muscle groups in older versus younger adults. The expression levels of the six core IPRGs were quantified via qRT-PCR.\nResults: A total of 44 elderly samples and 68 young healthy samples were analyzed for DEGs. Compared to young healthy muscle tissue, T cell infiltration levels in aged muscle tissue were significantly reduced, while mast cell and monocyte infiltration levels were relatively elevated. A new diagnostic screening model for sarcopenia based on the six IPRGs demonstrated high predictive efficiency (AUC = 0.871). qRT-PCR results indicated that the expression trends of these six IPRGs aligned with those observed in the database.\nConclusion: Six biomarkers-BTG2, FOXO3, AQP9, GPC3, CYCS, and SCN1B-were identified alongside a diagnostic model that offers a novel approach for early diagnosis of sarcopenia.", "claims": [{"id": "claim-method", "statement": "Based on IPRGs, LASSO regression analysis was performed using R software package “glmnet” (Friedman et al., 2010) to identify key genes related to sarcopenia.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39777262", "locator": "sections[14] \"Screening biomarkers and construction of the diagnostic nomogram model\" paragraph 2", "quote": "Based on IPRGs, LASSO regression analysis was performed using R software package “glmnet” (Friedman et al., 2010) to identify key genes related to sarcopenia."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding authors.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39777262", "locator": "sections[22] \"Data availability statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding authors."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Six biomarkers—BTG2, FOXO3, AQP9, GPC3, CYCS, and SCN1B—were identified alongside a diagnostic model with a training-set AUC of 0.871.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39777262", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "Six biomarkers—BTG2, FOXO3, AQP9, GPC3, CYCS, and SCN1B—were identified alongside a diagnostic model that offers a novel approach for early diagnosis of sarcopenia."}, {"asset": "source:pmid:39777262", "locator": "sections[6] \"Development and validation of the model for sarcopenia\" paragraph 2", "quote": "The model demonstrated promising performance, with an AUC of 0.871 on the training dataset (Figure 5B) and an AUC of 0.825 on the test dataset (Figure 5C)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Six biomarkers—BTG2, FOXO3, AQP9, GPC3, CYCS, and SCN1B—were identified alongside a diagnostic model with a training-set AUC of 0.871.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:39777262"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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